US11448589B2 - Analyzer, analysis method, and a program recording medium recorded with a program for analyzer - Google Patents
Analyzer, analysis method, and a program recording medium recorded with a program for analyzer Download PDFInfo
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- US11448589B2 US11448589B2 US16/912,050 US202016912050A US11448589B2 US 11448589 B2 US11448589 B2 US 11448589B2 US 202016912050 A US202016912050 A US 202016912050A US 11448589 B2 US11448589 B2 US 11448589B2
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- 238000004458 analytical method Methods 0.000 title claims abstract description 62
- 238000005259 measurement Methods 0.000 claims abstract description 103
- 229930195733 hydrocarbon Natural products 0.000 claims abstract description 98
- 150000002430 hydrocarbons Chemical class 0.000 claims abstract description 98
- 239000004215 Carbon black (E152) Substances 0.000 claims abstract description 96
- 238000004364 calculation method Methods 0.000 claims abstract description 78
- 238000001228 spectrum Methods 0.000 claims abstract description 64
- 230000001678 irradiating effect Effects 0.000 claims abstract description 9
- VNWKTOKETHGBQD-UHFFFAOYSA-N methane Chemical compound C VNWKTOKETHGBQD-UHFFFAOYSA-N 0.000 claims description 108
- 238000010801 machine learning Methods 0.000 claims description 40
- VGGSQFUCUMXWEO-UHFFFAOYSA-N Ethene Chemical compound C=C VGGSQFUCUMXWEO-UHFFFAOYSA-N 0.000 claims description 31
- 239000005977 Ethylene Substances 0.000 claims description 29
- 125000004805 propylene group Chemical group [H]C([H])([H])C([H])([*:1])C([H])([H])[*:2] 0.000 claims description 27
- QQONPFPTGQHPMA-UHFFFAOYSA-N propylene Natural products CC=C QQONPFPTGQHPMA-UHFFFAOYSA-N 0.000 claims description 25
- 239000007789 gas Substances 0.000 claims description 24
- 238000005033 Fourier transform infrared spectroscopy Methods 0.000 claims description 14
- 238000002485 combustion reaction Methods 0.000 claims description 8
- 239000003054 catalyst Substances 0.000 claims description 7
- 239000000446 fuel Substances 0.000 claims description 7
- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 claims description 6
- 239000000203 mixture Substances 0.000 claims description 6
- 239000001301 oxygen Substances 0.000 claims description 6
- 229910052760 oxygen Inorganic materials 0.000 claims description 6
- 238000012935 Averaging Methods 0.000 claims description 4
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 claims description 3
- 229910052799 carbon Inorganic materials 0.000 claims description 3
- 229910001872 inorganic gas Inorganic materials 0.000 claims description 3
- 239000004071 soot Substances 0.000 claims description 3
- 238000013500 data storage Methods 0.000 abstract description 29
- 239000000523 sample Substances 0.000 description 57
- 238000000862 absorption spectrum Methods 0.000 description 11
- 238000012545 processing Methods 0.000 description 9
- 238000011088 calibration curve Methods 0.000 description 5
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- 238000002347 injection Methods 0.000 description 2
- 239000007924 injection Substances 0.000 description 2
- 229910004613 CdTe Inorganic materials 0.000 description 1
- UFHFLCQGNIYNRP-UHFFFAOYSA-N Hydrogen Chemical compound [H][H] UFHFLCQGNIYNRP-UHFFFAOYSA-N 0.000 description 1
- 230000003466 anti-cipated effect Effects 0.000 description 1
- 238000000149 argon plasma sintering Methods 0.000 description 1
- 239000012159 carrier gas Substances 0.000 description 1
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- 238000004868 gas analysis Methods 0.000 description 1
- 229910052736 halogen Inorganic materials 0.000 description 1
- 239000001307 helium Substances 0.000 description 1
- 229910052734 helium Inorganic materials 0.000 description 1
- SWQJXJOGLNCZEY-UHFFFAOYSA-N helium atom Chemical compound [He] SWQJXJOGLNCZEY-UHFFFAOYSA-N 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
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- 238000001745 non-dispersive infrared spectroscopy Methods 0.000 description 1
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Images
Classifications
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
- G01N21/3504—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light for analysing gases, e.g. multi-gas analysis
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/0004—Gaseous mixtures, e.g. polluted air
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
- G01N21/3504—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light for analysing gases, e.g. multi-gas analysis
- G01N2021/3509—Correlation method, e.g. one beam alternating in correlator/sample field
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
- G01N2021/3595—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light using FTIR
Definitions
- the present invention relates to an analyzer to analyze a measurement sample on the basis of spectrum data obtained by irradiating light to the measurement sample.
- THC total hydrocarbon
- the FID analyzer is excellent in analysis precision, however, it is necessary to supply hydrogen gas (H 2 ) as supporting gas and helium gas (He) as carrier gas. Thus, there are problems, such as difficult handling and an increase in running costs.
- Patent Document 1 discloses that measurement precision is improved by previously calculating a correlation between a spectrum obtained by the FTIR analyzer and a concentration of THC indicated by the spectrum, followed by calculating a concentration of THC from the spectrum of a measurement sample by using the correlation.
- Patent Document 1 WO2019/031331
- Patent Document 1 intended to calculate the THC concentration from the spectrum of the measurement object by using the correlation, the measurement precision varies due to a difference in composition of components in exhaust gas. Consequently, the THC concentration cannot be calculated precisely in some cases if a specific fuel is used or under specific combustion conditions.
- absorbance may be saturated in an obtainable spectrum. Also in this case, it is difficult to precisely calculate the THC concentration on the basis of an obtained spectrum.
- a main anticipated problem of the present invention is to provide an analyzer, such as an FTIR analyzer, which achieves highly precise measurement of THC concentration in the measurement sample.
- the concentration calculation part selects at least one correlation data from among the plurality of correlation data stored in the correlation data storage part according to the concentration of the predetermined hydrocarbon component calculated by the main analysis part, and calculates a THC concentration in the measurement sample by using one correlation data thus selected.
- the plurality of correlation data each indicating a correlation between the concentration of the predetermined hydrocarbon component or the spectrum data and the THC concentration are contained in the analyzer, and the correlation data are selectable according to the concentration of the predetermined hydrocarbon component. It is therefore possible to calculate the THC concentration by using an appropriate correlation according to the composition or the like of the measurement sample. This leads to a highly precise calculation of the THC concentration even if a specific fuel is used or under specific combustion conditions.
- the correlation data storage part stores therein, as the plurality of correlation data, a first correlation data indicating a correlation between the concentration of the predetermined hydrocarbon component or the spectrum data and the THC concentration, and a second correlation data indicating a correlation different from the first correlation data.
- the concentration calculation part selects the first correlation data or the second correlation data from among the plurality of correlation data stored in the correlation data storage part according to the concentration of the predetermined hydrocarbon component calculated by the main analysis part, and calculates a THC concentration in the measurement sample by using the correlation data thus selected.
- the correlation indicated by the second correlation data may be a correlation of a kind different from or identical to that of a correlation indicated by the first correlation data.
- both the first correlation data and the second correlation data may indicate a correlation between a concentration of the predetermined hydrocarbon component and the THC concentration.
- the first correlation data may indicate a correlation between a concentration of the predetermined hydrocarbon component and the THC
- the second correlation data may indicate a correlation between the spectrum data and the THC concentration.
- the first correlation data is at least one rule-based calculation model for calculating the THC concentration from the concentration of the predetermined hydrocarbon component on the basis of the correlation between the concentration of the predetermined hydrocarbon component and the THC concentration.
- the second correlation data is at least one machine learning model calculated by machine learning of a correlation between the spectrum data and the THC concentration.
- the concentration calculation part calculates the THC concentration from the spectrum data by using the at least one rule-based calculation
- a concentration of a component other than the predetermined hydrocarbon component for example, a concentration of a hydrocarbon component other than methane, ethylene and propylene exceeds a predetermined value, such as a lower limit level of measurement, in the analyzer, there is a possibility that a hydrocarbon component whose concentration is not yet calculated by the analyzer is contained in the measurement sample. Therefore, the THC concentration calculated from the rule-based calculation model by using the concentration of the hydrocarbon component is liable to have a large deviation from a real value.
- the main analysis part preferably also analyzes a concentration of a component other than the predetermined hydrocarbon component in the total hydrocarbon component.
- the concentration calculation part preferably calculates the THC concentration from the concentration of the predetermined hydrocarbon component by using the first correlation data (specifically, a rule based calculation model) if the concentration of the component other than the predetermined hydrocarbon component calculated by the main analysis part is a predetermined value or below.
- the concentration calculation part preferably calculates the THC concentration from the spectrum data by using the second correlation data (specifically, a machine learning model) if the concentration of the component other than the predetermined hydrocarbon component calculated by the main analysis part exceeds the predetermined value.
- a specific embodiment of the predetermined hydrocarbon component is at least one selected from among methane (CH 4 ), ethylene (C 2 H 4 ) and propylene (C 3 H 6 ).
- a specific embodiment of the first correlation data is a rule-based calculation model for calculating the THC concentration from the concentration of the predetermined hydrocarbon component and its weighting factor which is the number of carbon molecules contained in the predetermined hydrocarbon component.
- the THC concentration calculation part preferably has a function of determining, by machine learning, one correlation data to be selected on the basis of information about correlation data selected in past, or information about one or more surrounding situations selected from among values related to physical attributes of the measurement sample, engine combustion information, engine head shape, ignition timing, catalyst composition, amount of oxygen in fuel, inorganic gas component, soot concentration, SOF concentration, engine type, engine speed, load information, hot start, cold start, oxygen concentration, catalyst temperature, and gear ratio.
- the concentration calculation part preferably selects two or more from among the plurality of correlation data, calculates two or more THC concentration by using two or more correlation data thus selected, and determines a THC concentration in the measurement sample by averaging the two or more THC concentrations thus calculated.
- the THC concentration is calculated using a more appropriate correlation according to an analysis result obtained by the main analysis part, thus leading to further enhanced calculation precision.
- the measurement sample is automotive exhaust gas.
- the analyzer is preferably of so-called FTIR method using Fourier transform infrared spectroscopy.
- an analysis method is intended to analyze a measurement sample on the basis of spectrum data obtained by irradiating light to the measurement sample.
- the analysis method includes a main analysis step, a correlation data storage step and a concentration calculation step.
- the main analysis step is intended to calculate a concentration of a predetermined hydrocarbon component contained in the measurement sample on the basis of the spectrum data of the measurement sample.
- the correlation data storage step is intended to store therein a plurality of correlation data each indicating a correlation between a concentration of the predetermined hydrocarbon component or the spectrum data and a THC concentration.
- the concentration calculation step is intended to select at least one correlation data from among the plurality of correlation data stored in the correlation data storage step according to the concentration of the predetermined hydrocarbon component calculated by the main analysis step, followed by calculating a THC concentration in the measurement sample by using one correlation data thus selected.
- a program recording medium recorded with a program is intended for an analyzer to analyze a measurement sample on the basis of spectrum data obtained by irradiating light to the measurement sample.
- the program for the analyzer causes a computer to perform functions as a main analysis part, a correlation data storage part and a concentration calculation part.
- the main analysis part calculates a concentration of a predetermined hydrocarbon component contained in the measurement sample on the basis of the spectrum data of the measurement sample.
- the correlation data storage part stores therein a plurality of correlation data each indicating a correlation between a concentration of the predetermined hydrocarbon component or the spectrum data and a THC concentration.
- the concentration calculation part selects at least one correlation data from among the plurality of correlation data stored in the correlation data storage part according to the concentration of the predetermined hydrocarbon component calculated by the main analysis part, and calculates a THC concentration in the measurement sample by using one correlation data thus selected.
- the above analysis method and the above program recording medium recorded with a program for the analyzer are capable of offering the same effects as the analyzer in the present invention described above.
- the analyzer such as the FTIR analyzer, which achieves highly precise measurement of the THC in the measurement sample.
- FIG. 1 is a general diagram of an exhaust gas measurement system including an analyzer in one of embodiments of the present invention
- FIG. 2 is a schematic diagram illustrating the entirety of the analyzer in the embodiment
- FIG. 3 is a functional block diagram of an arithmetic processing part in the embodiment.
- FIG. 4 is a functional block diagram of an arithmetic processing part in other embodiment.
- the analyzer 100 is an analyzer using Fourier transform infrared spectroscopy (FTIR) including, for example, an infrared light source 1 , an interferometer (spectral part) 2 , a measurement cell 3 , a photodetector 4 and an arithmetic processing part 5 as illustrated in FIG. 2 .
- the analyzer 100 (hereinafter also referred to as the FTIR analyzer 100 for the sake of distinction) is used as an exhaust gas analyzer to measure a concentration of total hydrocarbon (hereinafter also referred to as THC concentration) in exhaust gas as a measurement sample.
- THC concentration concentration of total hydrocarbon
- the infrared light source 1 irradiates infrared light having a broad spectrum (continuous light including lights of a large number of wavenumbers).
- a tungsten halogen lamp or high-brightness ceramic light source is used as the infrared light source 1 .
- the interferometer 2 is one which uses a so-called Michelson interferometer including a half mirror (beam splitter) 21 , a stationary mirror 22 and a movable mirror 23 as illustrated in FIG. 2 .
- Infrared light from the infrared light source 1 which has entered the interferometer 2 is divided into reflected light and transmitted light by the half mirror 21 .
- One of the lights is reflected by the stationary mirror 22 , and the other is reflected by the movable mirror 23 . Both return to the half mirror 21 and are combined and output from the interferometer 2 .
- the measurement cell 3 is a transparent cell that permits introduction of sampled exhaust gas. It is configured so that light output from the interferometer 2 passes through the exhaust gas in the measurement cell 3 into the photodetector 4 .
- the photodetector 4 detects infrared light after passing through the exhaust gas and outputs a detection signal (light intensity signal) thereof to the arithmetic processing part 5 .
- the photodetector 4 is an MCT (Hg CdTe) detector in the present embodiment, but may be a photodetector including other infrared detection element.
- the arithmetic processing part 5 calculates transmitted light spectrum data indicating a spectrum of the light transmitted through a sample from an output value from the photodetector 4 as illustrated in FIG. 3 , by cooperation between the CPU and peripheral devices thereof according to a predetermined program stored in the memory.
- the arithmetic processing part 5 calculates infrared absorption spectrum data from the transmitted light spectrum data, thereby determining various components in the exhaust gas.
- the arithmetic processing part 5 also performs a function as a main analysis part 51 to calculate concentrations of the individual components.
- the main analysis part 51 includes a spectrum data generation part 511 and an individual component analysis part 512 .
- the correlation data storage part 52 is one which is set to a predetermined region in the memory and stores therein a plurality of correlation data each indicating a correlation between a concentration of a predetermined hydrocarbon component calculated by the individual component analysis part 512 or spectrum data generated by the spectrum data generation part 511 , and a THC concentration in the measurement sample.
- the correlation data storage part 52 includes, as the correlation data, at least one first correlation data that is a rule-based calculation model for calculating a THC concentration from the concentration of the predetermined hydrocarbon component, and at least one second correlation data that is a machine learning model calculated by machine learning of the correlation between the spectrum data and the THC concentration.
- predetermined hydrocarbon component denotes methane (CH 4 ), ethylene (C 2 H 4 ) and propylene (C 3 H 6 ).
- THC denotes a THC concentration
- [CH 4 ], [C 2 H 4 ], [C 3 H 6 ] and the like are concentrations of individual hydrocarbon components, and a 1 , a 2 , a 3 . . . are weighting factors.
- the machine learning model indicated by the second correlation data is one which is previously calculated by a machine learning device disposed separately from the analyzer 100 , and stored in the correlation data storage part 52 as learned data.
- a THC concentration of the reference sample is measured using the FID analyzer, and the reference sample is also introduced into the FTIR analyzer so as to obtain absorption spectrum data thereof.
- the measured THC concentration and the obtained absorption spectrum data are linked into reference sample data.
- the machine learning model is obtainable by preparing a plurality of the reference sample data and by calculating, through machine learning, a correlation between the absorption spectrum data and the THC concentration.
- the THC concentration calculation part 53 in the present embodiment selects the first correlation data if a concentration of a hydrocarbon component of any one of methane, ethylene and propylene in concentrations of individual hydrocarbon components calculated by the main analysis part 51 exceeds a predetermined value (specifically, a lower limit of measurement, namely, a noise level), and if all the concentrations of hydrocarbon components other than methane, ethylene and propylene are the predetermined value (specifically, the lower limit of measurement, namely, the noise level) or below. Then, the THC concentration calculation part 53 calculates the THC concentration in the measurement sample by applying the concentrations of the individual hydrocarbon components calculated by the main analysis part 51 to the operation model indicated by the selected first correlation data.
- a predetermined value specifically, a lower limit of measurement, namely, a noise level
- [C 3 H 6 ] (M) is a propylene concentration in a measurement sample calculated by the individual component analysis part 512 .
- the THC concentration calculation part 53 may select either one of the first correlation data and the second correlation data if all the concentrations of methane, ethylene and propylene calculated by the main analysis part 51 are the predetermined value (noise level) or below, and if the concentrations of all hydrocarbon components other than methane, ethylene and propylene are the predetermined value (noise level) or below.
- the analyzer 100 With the analyzer 100 thus configured, the plurality of correlation data each indicating the correlation between the predetermined hydrocarbon component concentrations or the spectrum data and the THC concentration are contained therein, and the correlation data are selectable according to the hydrocarbon component concentration calculated by the main analysis part 51 . It is therefore possible to calculate the THC concentration by using an appropriate correlation according to the composition or the like of the measurement sample. This leads to a highly precise calculation of the THC concentration even if a specific fuel is used or under specific combustion conditions.
- the THC concentration calculation part 53 selects the rule-based calculation model (namely, the first correlation data). If the concentration of any one of hydrocarbon components other than methane, ethylene and propylene exceeds the noise level or below, the THC concentration calculation part 53 selects the machine learning model (namely, the second correlation data).
- the rule-based calculation model namely, the first correlation data
- the THC concentration calculation part 53 selects the machine learning model (namely, the second correlation data).
- the THC concentration calculation part 53 may select the rule-based calculation model (namely, the first correlation data), and may calculate a THC concentration of a measurement sample on the basis of the rule-based calculation model.
- the THC concentration calculation part 53 may select the machine learning model (the second correlation data), and may calculate a THC concentration of a measurement sample on the basis of the machine learning model.
- the THC concentration calculation part 53 may select the machine learning model and calculate a THC concentration in a measurement sample by applying the spectrum data to the machine learning model.
- the THC concentration calculation part 53 may be configured to select optimum second correlation data from among the plurality of second correlation data stored in the correlation data storage part 52 by machine learning upon receipt of an analysis result obtained by the main analysis part 51 (spectrum data and individual component concentration data). Specifically, in terms of the plurality of stored different machine learning models (second correlation data), the THC concentration calculation part 53 may be configured to find regularity (clustering) by machine learning on the basis of individual HC component concentrations and spectrum data characteristics. For example, the regularity may be found out by k-means and other method.
- the THC concentration calculation part 53 may select two or more from among the plurality of correlation data, and may calculate a THC concentration on the basis of the selected two or more correlation data. For example, a new correlation may be calculated by averaging correlations individually indicated by a plurality of different correlation data with the use of various techniques, such as arithmetic mean and weighted average, and a THC concentration may be calculated on the basis of the calculated correlation. Alternatively, a new correlation may be calculated by machine learning from correlations indicated by a plurality of selected correlation data.
- a plurality of THC concentrations may be calculated on the basis of correlations individually indicated by the plurality of selected correlation data, and a THC concentration in a measurement sample may be calculated by averaging a plurality of calculated THC concentrations.
- selecting a plurality of correlation data only a plurality of first correlation data may be selected, only a plurality of second correlation data may be selected, or at least one first correlation data and at least one second correlation data may be selected.
- a correlation expressed by the machine learning model indicated by the second correlation data may employ, as a parameter, information about the surrounding situations, such as measurement conditions.
- the surrounding situations include values related to physical attributes, such as temperature and pressure of a measurement sample, combustion information about an engine (information related to supercharging, EGR, rich/stoichiometric/lean, laminar flow, uniform flow, direct injection, and port injection), engine head shape, ignition timing, catalyst composition, amount of oxygen in fuel, inorganic gas component, soot concentration, SOF concentration, engine type, engine speed, load information, hot start, cold start, oxygen concentration, catalyst temperature, and gear ratio.
- a correlation expressed by the machine learning model may employ, as a parameter, a part or all of these surrounding situations. Alternatively, only surrounding situations that strongly affect (are highly related to) a THC concentration calculated by the analyzer 100 may be employed as a parameter.
- the exhaust measurement system in the present embodiment is intended to test a completed vehicle V by using the chassis dynamometer 300 .
- the system may be intended to test engine performance by using, for example, an engine dynamometer, or test power train performance by using the dynamometer.
- the analyzer 100 may be configured to irradiate light to a measurement sample so as to make an analysis from a spectrum thereof.
- the analyzer 100 is also applicable to NDIR and ones other than spectroscopic analyzers, such as light scattering particle size distribution measuring device.
- the present invention is not limited to an automotive exhaust gas analysis, but is also capable of analyzing exhaust gas of internal combustion engines of, for example, ships, aircrafts, agricultural machinery and machine tools.
Abstract
Description
[THC]=a 1.[CH4]+a 2.[C2H4]+a 3.[C3H6]+ . . . (1)
As used here, the term [THC] denotes a THC concentration, [CH4], [C2H4], [C3H6] and the like are concentrations of individual hydrocarbon components, and a1, a2, a3 . . . are weighting factors.
[THC]=[CH4] (2)
[THC]=[CH4]+2.[C2H4] (3)
[THC]=[CH4]+2.[C2H4]+3.[C3H6]. (4)
[THC](M)=[CH4](M) (5)
[THC](M)=[CH4](M)+2.[C2H4](M) (6)
[THC](M)=[CH4](M)+2.[C2H4](M))+3.[C3H6](M) (7)
- 100 analyzer
- 51 main analysis part
- 52 correlation data storage part
- 53 THC concentration calculation part (concentration calculation part)
Claims (12)
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JP2019117758A JP6964114B2 (en) | 2019-06-25 | 2019-06-25 | Analyzer, analysis method and program for analyzer |
JP2019-117758 | 2019-06-25 |
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